Evaluate the integral
\nwhere
\nIf , compute .
[THOUGHT] We need to evaluate the integral:
where is a degree-7 polynomial with complex coefficients. The integrand has a pole at in the complex plane. Since the exponential is . For convergence of the integral along the real axis, we need the factor to decay as in the upper or lower half-plane. Actually, with real: , magnitude 1. So it doesn't decay. Wait, but the integral is over real , so the integrand is where . The denominator grows as for large real , so the integral converges absolutely because polynomial numerator times (bounded) divided by yields decay like (since degree of numerator is 7, denominator degree 8). So it's absolutely convergent.
But to evaluate, we can consider contour integration in the complex plane. The integrand is analytic except at the pole where . The exponential factor decays in the upper half-plane if because . So for , magnitude decays. Since our pole is at , it lies in the upper half-plane. To apply the residue theorem, we close the contour in the upper half-plane (where decays). However, we must check if the semicircular arc at infinity contributes zero. For large in the upper half-plane, if . But for the arc with , , we have , so . However, the denominator grows as , so the integrand decays as times bounded exponential. So the arc contribution vanishes as . Therefore,
The residue at a pole of order 8 is given by:
where . Here , . So:
Thus,
We need to compute , take its 7th derivative, evaluate at , multiply by , then find , , compute .
We can do this with symbolic computation in Python using sympy. However, derivatives of order 7 might be heavy but doable. Let's define . Compute as given, then compute derivative.
But note: is a polynomial with complex coefficients. We'll compute exactly using sympy rationals? Might be messy. Let's use sympy's derivative and simplify.
We'll compute . Then compute . Evaluate at . Then compute .
We need numeric values for a and b. Use high precision? Might be large numbers. Use mpmath or sympy's N with high precision.
Let's implement.
First, import sympy, define symbols, define P(x) as given, compute derivative, substitute, evaluate numerically.
We need to be careful with complex i. Use sympy.I.
Let's code. </think>
[PYTHON] import sympy as sp
Define symbols
x = sp.symbols('x', complex=True) I_sym = sp.I
Define c = 205/69
c = sp.Rational(205, 69)
Define P(x) as given
P = (x7 - 14I_symx6 + (85 - 60*I_sym)x**5 - (240 + 210I_sym)x**4 + (420 - 840I_sym)x**3 - (560 + 1680I_sym)x**2 + (1344 - 2688I_sym)*x + 3840)
Define f(z) = P(z) * exp(I*z)
z = sp.symbols('z', complex=True) f = P.subs(x, z) * sp.exp(I_sym * z)
Compute 7th derivative
f7 = sp.diff(f, z, 7)
Evaluate at z = I*c
point = I_sym * c f7_at_point = f7.subs(z, point)
Compute I = 2Ipi / 7! * f7_at_point
I_val = (2 * sp.pi * I_sym / sp.factorial(7)) * f7_at_point
Simplify (might be heavy)
I_simplified = sp.simplify(I_val)
Convert to numeric (high precision)
I_numeric = sp.N(I_simplified, 30) # 30 digits
Extract real and imaginary parts
a = sp.re(I_numeric) b = sp.im(I_numeric)
print("I =", I_numeric) print("Real part a =", a) print("Imaginary part b =", b) print("Floor(10a) =", sp.floor(10a)) print("Floor(b) =", sp.floor(b)) print("Floor(10a) + Floor(b) =", sp.floor(10a) + sp.floor(b)) [/PYTHON]
[THOUGHT]
The Python output gives and .
Then and .
Sum = .